Tomer Shiran, MapR_Hadoop&SQL
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This document discusses SQL support for Hadoop including Apache Hive, Drill, Impala, and others. It notes that MapR provides broad SQL support including faster Impala performance. Drill 1.0 is slated for an alpha release this month. Hadoop BI tools can do more than just SQL queries.
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Tomer Shiran, MapR_Hadoop&SQL
- 1. SQL-in-Hadoop • SQL is hot again! Apache Hive (+ Stinger/Tez) Apache Drill Shark/Spark Impala Phoenix Greenplum (HAWQ) Cascading Lingual Hadapt Splice Machine • MapR provides the broadest SQL support Apache Hive 0.11 GA Impala on MapR Private beta (25-50% faster) Apache Drill 1.0 Alpha this month • Hadoop BI tools can do a lot more than SQL queries
- 2. Why Apache Drill? • Community-driven project – SQL is an application interface – Users don’t want vendor lock-in • Next-generation SQL-in-Hadoop – Full ANSI SQL:2003 – Schema is optional – Nested data: JSON, Protobuf, … – Highly extensible – YARN integration Who’s contributing? MapR Pentaho Oracle VMWare Microsoft Thoughtworks UT Austin UW Madison RJMetrics XingCloud Lines of code: > 100K
- 3. It’s Not Just About Queries… • Real-time data loading so you don’t query stale data – HDFS was not designed for these workloads • Common storage and resource mgmt for all Big Data applications – Enterprise-grade: HA, DP (snapshots), DR (mirrors) – Multi-tenancy – Read/write access (POSIX) MapRDistributed Data System (MDDS) YARN Batch (MapReduce) SQL (Drill, Tez, Impala) Search (Solr, Elasticsearch) Streaming (Storm) File-based (POSIX) Table-based (MDDS, HBase) MapRDistribution for Apache Hadoop